No abstract

In data centers, workload consolidation is the common method to improve resource utilization. However, efficient workload consolidation faces challenges from two aspects: the first is the wide variety of program characteristics; the second is the multiple performance indexes in clusters or data centers, such as the program performance requirement from custom and the system utilization from the cluster provider. In this paper, multiple experiments are executed about program performance with restricted resource usage, and four conclusions are summarized. Then based on the conclusions, two individualized precise scheduling strategies are proposed for efficient consolidation. Sche-index2 schedule programs by considering the resource sensitivity hyper-plane on five resource dimensions, and Sche-utility scheduling programs by considering the sensitivity curve of five resource dimensions. The experiment results show that compared with the common scheduling strategy, Sche-index2 can improve the average performance of the program by 36%, and Sche-utility can improve the average performance of the program by 27.6%. Meanwhile, both of the scheduling strategies can improve the resource utilization of CPU, disk read/write bandwidth, memory, and network bandwidth.